Evidence map›Paper›PMID 33632140›Full record

ArticleBMC infectious diseases2021

Monitoring HIV testing and pre-exposure prophylaxis information seeking by combining digital and traditional data.

Derek C Johnson, Alicia L Nobles, Theodore L Caputi, Michael Liu, Eric C Leas, Steffanie A Strathdee, Davey M Smith, John W Ayers

Abstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Detection ofJournal of water and health · 2024
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Derek C JohnsonDepartment of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, California, 92093, USA. dcjohnson@ucsd.edu.
Alicia L NoblesDepartment of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, California, 92093, USA.
Theodore L CaputiThe Center for Data Driven Health at the Qualcomm Institute, University of California San Diego, La Jolla, California, USA.
Michael LiuUniversity of Oxford, Oxford, UK.
Eric C LeasThe Center for Data Driven Health at the Qualcomm Institute, University of California San Diego, La Jolla, California, USA.
Steffanie A StrathdeeDepartment of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, California, 92093, USA.
Davey M SmithDepartment of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, California, 92093, USA.
John W AyersDepartment of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, California, 92093, USA.

Funding

Training Program in Substance Use, HIV and Related InfectionsT32DA023356 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Natasha Martin, Steffanie A Strathdee · 2007 to 2026
$7.8M
Impact of Drug Policy Reform on the HIV Risk Environment among IDUs in TijuanaR37DA019829 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI STRATHDEE, STEFFANIE A. · 2010 to 2019
$6.7M
Quantifying Treatment Help-Seeking Among Self-Identified Opioid Users on Social MediaK25DA049944 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NOBLES, ALICIA · 2020 to 2021
$339k
NIDA NIH HHS K25 DA049944NIDA NIH HHS R37 DA019829NIDA NIH HHS T32 DA023356
6 · The paper itself

Abstract

backgroundPublic health is increasingly turning to non-traditional digital data to inform HIV prevention and control strategies. We demonstrate a parsimonious method using both traditional survey and internet search histories to provide new insights into HIV testing and pre-exposure prophylaxis (PrEP) information seeking that can be easily extended to other settings.

methodWe modeled how US internet search volumes from 2019 for HIV testing and PrEP compared against expected search volumes for HIV testing and PrEP using state HIV prevalence and socioeconomic characteristics as predictors. States with search volumes outside the upper and lower bound confidence interval were labeled as either over or under performing. State performance was evaluated by (a) Centers for Disease Control and Prevention designation as a hotspot for new HIV diagnoses (b) expanding Medicaid coverage.

resultsTen states over-performed in models assessing information seeking for HIV testing, while eleven states under-performed. Thirteen states over-performed in models assessing internet searches for PrEP information, while thirteen states under-performed. States that expanded Medicaid coverage were more likely to over perform in PrEP models than states that did not expand Medicaid coverage. While states that were hotspots for new HIV diagnoses were more likely to over perform on HIV testing searches.

conclusionOur study derived a method of measuring HIV and PrEP information seeking that is comparable across states. Several states exhibited information seeking for PrEP and HIV testing that deviated from model assessments. Statewide search volume for PrEP information was affected by a state's decision to expand Medicaid coverage. Our research provides health officials with an innovative way to monitor statewide interest in PrEP and HIV testing using a metric for information-seeking that is comparable across states.

Indexed as

Information Seeking BehaviorHIV InfectionsHIV TestingHumansInternetMedicaidPre-Exposure ProphylaxisPrevalenceUnited StatesGoogle trendsHIVHIV testingInternetPrEP

Identifiers

PMID33632140
PMCPMC7908754

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.